In my column last week, I discussed the importance of professional “stretching” as a tool to continually challenge ourselves to reach new goals. Since my stretching exercise happens this week when I speak on the topic of “Killer Social Intelligence Mining” at Digital Pharma West in San Francisco, I thought it would be prudent to give a preview of that session here, today.
Social intelligence is an intriguing topic.
I’ve long regarded search query data as a clear manifestation of customer needs and wants. Search engine users go to great lengths to precisely articulate what they’re in search of. There’s power in harnessing that intelligence. It allows search marketers to speak the language of prospective customers, and meet the needs of site visitors after the click. Yet, despite all the power that search query data alone holds, augmenting that intelligence with social data can prove to be infinitely more powerful.
All modern-day social marketers are leveraging some type of social “listening” technology. The data those platforms return is undeniably beneficial, but there’s opportunity beyond mere listening. Everyone has access to listening tools; what they deliver is table stakes. Plus, there’s more, richer social data for us to tap into if we know where to look, and are committed to understanding more about our customers through iterative experimentation.
Here’s how to tap into social data that’s hovering at the periphery of most marketer’s line of sight, and creating a competitive advantage for your company.
Google’s Web Analytics Evangelist Avinash Kaushik introduces the simple, but powerful, measurement technique outcomes analysis in his book, “Web Analytics 2.0.” He offers this up in response to the hyper-focus most digital marketers place on conversion and clickstream analyses. Conversion and clickstream don’t tell us the whole story when conversion events primarily occur offline or in situations when our visitors are in a fact-finding mindset. Outcomes analysis defines success when users complete their intended tasks efficiently.
Judging social interactions, or clickthroughs from social properties is no different. Social should be considered a venue for peer-to-peer dialogue. The successful community manager will build and foster an environment conducive to that type of exchange. There are few instances where brand-to-consumer conversion-focused communications are appropriate here. Assess social conversations, and subsequent clickthrough behaviors, with an eye towards outcomes analysis to judge the efficacy of your social media efforts. Defining those KPIs properly will expose you to a wealth of consumer insight, and help your organization better define the role of social in the buying cycle (likely an assist, not a close).
In fact, properly defining KPIs is the real key to all of this. Marty Weintraub of Aimclear wrote a brilliant piece on proper social KPIs when he slammed GM’s move to shut off its Facebook advertising. Weintraub contends that GM hadn’t properly identified its Facebook strategy and therefore its social advertising efforts yielded underwhelming results. The moral of the story is: Define your objectives before ever kicking off a marketing campaign.
And do your research to better understand the opportunities available through social media. Facebook’s Ads tool is an exceptional way to perform ad hoc demographic/psychographic research. Just as users self-express much of their needs and wants via search queries, what they divulge about themselves as Facebook users is equally telling. We can put that knowledge to use as we craft persona-specific communication and site experiences.
Advanced Facebook Insights
Michael King (@ipullrank) wrote an exceptional how-to for implementing keyword-level demographics in Google Analytics by piping in Facebook Open Graph data through use of Custom Variables. Frankly, my mind is still spinning over it and the possibilities it presents. While it requires a bit of elbow grease, patience, and visitor opt-in, the type of demographic information it provides is invaluable. Not only will you be better informed of visitor demographics, but this information will also enable you to craft site experiences that specifically address the needs of your most critical audiences. That’s power.
Another interesting application for this data is to serve voice of customer analytics (on-site survey analytics) when certain demographic criteria are met.
Real-Time Rock Stardom
My friend Rob Garner is the authority on harnessing the real-time nature of search and social channels to maximize content engagement and (eventual) conversion. His article on “content velocity” is requisite reading for anyone serious about real-time customer centricity.
This is where it all comes full circle. Though social listening technologies are limited in utility for a number of reasons, the biggest handicap they face is in how they’re often applied. Many social programs begin with an ad hoc investigation into the online chatter surrounding a brand and/or industry vertical. The real benefit is in trending this analysis over an extended period of time. Only then will you be armed with the intelligence to compete across the real-time Web. At my firm we call this proactively reacting, or acting faster than our competition to an opportunity we’re observing as it takes shape.
Killer social intelligence mining means pushing back on the ad hoc mindset, and committing to understanding the marketplace through a smart application of available data and existing technologies.